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At least 1,279 records · Page 71Linked to original sources

Mapping the thermal landscape of the Upper Mississippi River

Temperature has a fundamental influence on physical, chemical and biological processing in aquatic ecosystems. River temperatures respond to a diverse array of drivers including air temperature, streamflow, and thermal inputs, but the physical template has been shown to play a significant role in structuring spatial and temporal variation in water temperature. How these factors interact to affect water temperature in complex floodplain river habitats such as those present in the Upper Mississippi River System (UMRS) is not well-studied. We used a combination of airborne thermal imagery and continuous temperature loggers deployed across aquatic area types to evaluate spatial and temporal patterns in water temperature in Navigation Pool 8 during the summer and fall of 2017. The mid-wave infrared thermal camera available for this study is not commonly used for thermal imagery acquisition over water, so we discuss accommodations that were made to account for potential interferences and describe considerations for future users interested in using the technology. We quantified thermal metrics from imagery and continuous loggers (e.g., mean, coefficient of variation, range) and compared those to hydrogeomorphic variability across aquatic areas using a Geographic Information System (GIS) dataset. Our findings showed that both temporal and spatial temperature patterns were linked to variation in depth and connectivity of aquatic areas across the pool. Despite some of the technical challenges associated with acquiring this imagery, the method shows promise for characterizing spatial variation in surface temperatures in the UMRS associated with complex physical features such as habitat rehabilitation and enhancement projects.

Iowa, Illinois, Minnesota, Wisconsin↗

Conventional rare earth element mineral deposits: The global landscape

Four conventional mineral deposit types—carbonatite, alkaline igneous, heavy mineral sand, and regolith-hosted ion-adsorption clay deposits—currently supply global markets with the rare earth elements (REEs) and rare earth oxides (REOs) necessary to meet the technological needs of global communities. The unique properties of REEs make them useful in a wide variety of applications, such as alloys, batteries, catalysts, magnets, phosphors, and polishing compounds. Rare earth element minerals are complex in both composition and structure. Carbonate, oxide, silicate, and phosphate-type minerals contain highly variable amounts of rare earths. Most rare earth-bearing minerals contain mainly lighter rare earths, a mixture of all the rare earths, or only the heavier rare earths. Diverse technological applications require the full range of light, middle, and heavy rare earths. The production of these elements, in particular the heavy rare earths, remains highly dependent on deposits from China. Diversification of rare earth supply chains is contingent on expanded knowledge of globally distributed resources and an understanding of the degree to which those resources have been explored and evaluated. The knowledge of tectonic setting, typical rock associations, deposit morphology, and deposit genesis has led to the discovery of many conventional-type rare earth deposit types. Recent developments are anticipated to result in further discoveries that have the potential to meet the ever-expanding applications of REEs and REOs to address modern societal needs.

Book chapter↗

A monitoring framework to assess forest bird population response to landscape scale mosquito suppression using the Incompatible Insect Technique

The Birds, Not Mosquitoes Monitoring and Support Science Working Group detailed methods for monitoring the population response of Hawaiian forest birds during implementation of the Incompatible Insect Technique (IIT) on the islands of Maui and Kauaʻi. The group prioritized methods for measuring the influence of mosquito suppression on populations within IIT treatment and control areas and identified focal species for IIT efficacy monitoring in birds. Three primary metrics were established to assess the impact of IIT on vulnerable species: population demography, density, and geographic range. Each metric can be evaluated using multiple methods. This report reviews those methods, with emphasis on approaches supported by pre-IIT baseline data and compatible with a before-after control-impact (BACI) study design for evaluating population responses over time. Focal avian species were selected based on population size estimates, fecundity, and disease susceptibility. We identified ʻākohekohe (Palmeria dolei), ʻiʻiwi (Drepanis coccinea), Maui ʻalauahio (Paroreomyza montana), Hawaiʻi ʻamakihi (Chlorodrepanis virens), Kauaʻi ʻamakihi (Chlorodrepanis stejnegeri), Kauaʻi ʻelepaio (Chasiempis sclateri), and ʻanianiau (Magumma parva) as focal species for monitoring population level response to disease suppression. Populations of kiwikiu (Pseudonestor xanthophrys), ʻakikiki (Oreomystis bairdi), akekeʻe (Loxops caeruleirostris), and the ʻiʻiwi population on Kauaʻi may be too small (e.g., <100 individuals) to effectively monitor, and it is unlikely that sufficient data can be collected from these birds to show IIT efficacy in a relatively short time frame (i.e., 5–10 years). Despite the logistical challenges to IIT implementation, there is potential to maintain disease-free status in individual populations of birds. Indeed, the continued existence of these critically endangered species in the wild within or near IIT treatment areas could be considered an accomplishment of IIT, given the current predictions for their extinction in the wild within 5–10 years. Demographic monitoring methods, including territory mapping, nest monitoring, mist-netting, and mark-recapture studies, provide direct evidence of survivorship and reproductive output. When combined with disease surveillance, these approaches could provide the most robust evidence of increased survivorship and productivity resulting from avian malaria suppression via IIT. However, demographic studies require several years of monitoring to achieve statistically robust BACI comparisons of survivorship and are more difficult to implement relative to other approaches. Given that these field efforts are labor-intensive and heavily reliant on personnel availability and funding, demographic monitoring could be conducted when adequate resources permit. On both Maui and Kauaʻi, passive acoustic monitoring (PAM) was identified as a priority method for monitoring the range, occupancy, and relative abundance of focal species. Autonomous recording units (ARUs) can record bird vocalizations in remote areas for several months. Innovative machine learning techniques permit rapid and semi-autonomous identification of most endemic honeycreepers on each island, maximizing sampling efficiencies and minimizing data processing costs. We predict mosquito suppression could support expansion of focal species into areas where disease transmission is currently excluding these species and expect acoustic monitoring data of focal species to reflect these spatial patterns. Additionally, the relative occupancy and call densities can be monitored temporally and spatially to assess the efficacy of IIT for supporting positive growth in vulnerable bird species. It is not yet clear if PAM is more effective than other methods, such as distance sampling, for detecting trends in the densities of rare species. However, the increased detections resulting from the larger sample size per observation point using ARUs will likely improve accuracy in detecting changes in species’ ranges. Collection of during and after treatment data within the BACI design could help to provide critical information to track avian population response, recovery, and potential range expansion related to IIT efforts. Point-transect distance sampling (point-counts) was prioritized as a method for monitoring population densities of focal species. Extensive historical sampling across focal species’ ranges provides a robust baseline for detecting change. These counts provide updated population densities and can be used to assess the distribution of focal species within IIT treatment areas. However, detecting subtle population changes with traditional distance sampling requires intensive spatial and temporal effort and may be less effective for rare species. To improve resolution, density surface modeling can integrate multiple data sources (e.g., point-counts, PAM, spot-mapping, and resightings) to estimate species-specific densities at finer spatial scales, including within and outside IIT treatment areas. This integrated modeling approach allows for detailed comparisons and may reveal early signs of recovery, including recolonization of formerly occupied sites. A coordinated monitoring strategy can allow managers to evaluate the success of mosquito suppression as a conservation intervention and support adaptive management in the face of emerging challenges.

Hawaii↗